A system for analyzing and generating Italian texts is under development at the IBM Rome Scientific Center. Detailed semantic knowledge on word-sense patterns is used to relate the linguistic structure of a sentence to a conceptual representation (a conceptual graph). Conceptual graphs are stored in a database and accessed by a natural-language query/answering module. The system analyzes a text supplied by a press-agency-release database. It consists of three modules: a morphological, a syntactic, and a semantic processor. The semantic analyzer uses a conceptual lexicon of word-sense descriptions, currently including about 850 entries. A description is an extended case frame providing the surface semantic patterns (SSP) of a word-sense w. SSPs express both semantic constraints and word-usage information, such as commonly found word patterns, idioms, and metaphoric expressions. SSPs are used by the semantic interpreter to build a conceptual graph of the sentence, which is then accessed by the query-answering and language-generation modules. This paper makes the claim that the SSP approach is viable and necessary to cope with language phenomena in unrestricted domains. Surface patterns are easily acquired inductively from the natural-language corpus rather than deductively from predefined conceptual structures. SSPs map quite complex sentences into surface semantic representations that can be generalized at a subsequent stage. In contrast, the current state of the art does not provide viable theory or methodology to go from superficial to deep structures. This issue is more extensively addressed in the body of the paper.
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